Application Deadline:
05/07/2026
Address:
100 King Street West
Job Family Group:
Audit, Risk & Compliance
Success in this role depends on a strong foundation in AML AND model validation—particularly within AML and fraud models—paired with solid hands‑on skills in SAS, Python, and SQL.
Mandate
Assist the Senior Manager and Director of the AML & Fraud Model Validation (MV) team with enterprise-wide management of model risk so that the bank is not subject to unjustified (in a risk vs. return framework), undue, and unidentified risks due to the use of models and promoting the transparency and understanding of models and model risks used across the Bank in AML & Fraud areas. The mandate of this position is summarized as follows:
- Effectively identify risks associated with models; timely, accurately and independently assess models used in the areas of responsibility; and tactfully provide the recommendations to model owners and users to mitigate the risks
- Assist the Senior Manager to develop/continuously enhance model validation methodology; and conduct validation
- Ensure that the models (development, documentation, usage, etc.) in AML & Fraud areas are compliant with the Bank’s Enterprise Model Risk Framework, and are compliant with OSFI/FRB/OCC’s requirement
- Provide advisory support to large-scale projects as required and other work streams as appropriate and requested to ensure that bank’s models are in line with industry best practice
- Support the Senior Manager in the development and execution of overall work plan
Knowledge and Skills
Knowledge:
- Hands-on experience and advanced knowledge in AML or Fraud models (transaction monitoring, Watchlist Screening, Customer Risk Rating, credit card fraud, mar) etc.
- Good knowledge and relevant training in data mining, machine learning, and statistical analysis techniques, with minimal 3 years of demonstrated experience pertaining to AML/Fraud or machine learning/statistical modeling.
- In-depth knowledge of industry best practices;
- Good knowledge of regulatory requirements on AML models; experience in regulatory matters as an asset
- Minimum: Master’s Degree, PhD. preferred in a quantitative field e.g., Mathematics, Computer Science, Statistics and Engineering.
- AML Designation such as CAMS, ACAMS preferred
Skills:
- Detail-oriented, analytical, well organized, highly self-motivated and good interpersonal skills
- Effective time management in order to efficiently deliver concurrent projects with competing priorities
- Good ability of conflict-solving; and ability to collaboratively work with model owner/sponsor counterparts
- Effective presentation and communication skills; Ability to convey complex concepts and outcomes to non-subject matter experts.
- Proficiency in computing development skills, particularly statistical and database modeling tools (Python, SAS, R, SQL, Matlab, Access/VBA etc.). Ability to adapt to various programming languages and environments. Advanced SAS proficiency is required
Job Descriptions
Model Validation (75%)
- Support senior managers in the development and execution of overall work plan
- Manage assigned validation/review projects and ensure a timely delivery of the validation report with high quality.
- Support senior managers in the on-going monitoring of AML and Fraud models to identify early warning of model performance deterioration and ensure proper mitigation/action plan in place in such situations;
- Perform research and analysis of applicable methodologies; benchmark model owners’ approaches; and present and recommend appropriate alternative for model developers;
- Produce validation reports, with clarify of issues and actionable items, including recommendations, to help the lines of business enhance the validated model
- Ensure model inventory is accurate and up-to-date, reflecting the model attributes as evidenced in relevant documentations.
- Provide regular updates on the assigned vetting/review, including a regular review of models/methodologies implemented and ensure that high model risk issues are raised and addressed at appropriate management level
- Keep abreast with advances in credit risk analytics developments and applications by vendors, consultants, regulatory agencies and competitors. Recommend/develop enhancements appropriate for the Bank
Relationship Management (5%)
- Partner with the lines of business, corporate functions, and ERPM to enhance understanding of model risks relating to Corporate Risk models and ensure transparency of models used in their respective areas
- Build and manage relationships with the line of business/risk managers/executives in the joint implementation of strategic changes in the business by assisting model development via parallel-to-development model risk consulting. Act as internal consultant to proactively help the lines of business manage its’ model risk
- Provide support to large-scale projects as required and subject matter advisory support to other wo